In Heliyon
BACKGROUND : This study aimed to develop an artificial intelligence-based computer-aided diagnosis system (AI-CAD) emulating the diagnostic logic of radiologists for lymph node metastasis (LNM) in esophageal squamous cell carcinoma (ESCC) patients, which contributed to clinical treatment decision-making.
METHODS : A total of 689 ESCC patients with PET/CT images were enrolled from three hospitals and divided into a training cohort and two external validation cohorts. 452 CT images from three publicly available datasets were also included for pretraining the model. Anatomic information from CT images was first obtained automatically using a U-Net-based multi-organ segmentation model, and metabolic information from PET images was subsequently extracted using a gradient-based approach. AI-CAD was developed in the training cohort and externally validated in two validation cohorts.
RESULTS : The AI-CAD achieved an accuracy of 0.744 for predicting pathological LNM in the external cohort and a good agreement with a human expert in two external validation cohorts (kappa = 0.674 and 0.587, p < 0.001). With the aid of AI-CAD, the human expert's diagnostic performance for LNM was significantly improved (accuracy [95% confidence interval]: 0.712 [0.669-0.758] vs. 0.833 [0.797-0.865], specificity [95% confidence interval]: 0.697 [0.636-0.753] vs. 0.891 [0.851-0.928]; p < 0.001) among patients underwent lymphadenectomy in the external validation cohorts.
CONCLUSIONS : The AI-CAD could aid in preoperative diagnosis of LNM in ESCC patients and thereby support clinical treatment decision-making.
Zhang Shuai-Tong, Wang Si-Yun, Zhang Jie, Dong Di, Mu Wei, Xia Xue-Er, Fu Fang-Fang, Lu Ya-Nan, Wang Shuo, Tang Zhen-Chao, Li Peng, Qu Jin-Rong, Wang Mei-Yun, Tian Jie, Liu Jian-Hua
2023-Mar
18F-FDG PET/CT, 18-fluorine-fluorodeoxyglucose positron-emission tomography/computed tomography, AI, Artificial intelligence, AI-CAD, Artificial intelligence-based computer-aided diagnosis, Artificial intelligence, CI, Confidence interval, CT, Computed tomography, ESCC, Esophageal squamous cell carcinoma, Esophageal squamous cell carcinoma, LNM, Lymph node metastasis, Lymph node metastasis, OS, Overall survival, PET/CT, PFS, Progression-free survival, SD, Standard deviation, SLR, Ratio of the SUV value to liver uptake, SUV, Standardized uptake value, cN, Clinical N stage, nCRT, Neoadjuvant chemoradiotherapy, pN, Pathological N stage
